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Common operations like map and filter are available in parallelized form through PLINQ, though the names differ. A map can be achieved with PLINQ’s Select operator, and a filter with PLINQ’s Where operator. For example, I could implement a ParallelMap
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In this post, we’ll investigate some ways that Parallel Extensions can be used to introduce parallelism and asynchrony to I/O scenarios. Here’s a simple scenario. I want to retrieve data from a number of web resources. static string[] Resources = new
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One of the great features that crosses all of Parallel Extensions types is a consistent approach to cancellation (see http://blogs.msdn.com/pfxteam/archive/2009/05/22/9635790.aspx ). In this post we explore some of the ways cancellation is used in Parallel
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As Ed Essey explained in Partitioning in PLINQ , partitioning is an important step in PLINQ execution. Partitioning splits up a single input sequence into multiple sequences that can be processed in parallel. This post further explains chunk partitioning,
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We exert a good deal of effort ensuring that the APIs we provide are consistent within Parallel Extensions as well as with the rest of the .NET Framework. This is from many angles, including behavior and general design, but also naming. So
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Along with the release of the .NET Framework 4 Beta 1 , we've just published a slew of samples that demonstrate using Parallel Extensions in a variety of ways. You can download these from Code Gallery at http://code.msdn.microsoft.com/ParExtSamples .
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Brad Abrams posted about a cool .NET Framework 4.0 poster which was distributed at the PDC last week and which you can download . Zoom in on the CORE section right in the middle for a glimpse into the parallelism support in .NET 4.0.
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